tangle_cnn/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
tangle_cnn/__main__.py,sha256=Aykcq0R1Q7dh8uRpJ4W36RA_ooWbCfGDtniSDVoeQgs,76
tangle_cnn/blockface_to_multichannel.py,sha256=U3pG9UL7s4IQfqoPaw7igsLz8gJILyErqB3Ibv6vYrw,3545
tangle_cnn/levels.py,sha256=KWegrWRrMV34GL_TDnQD2OzB3VClhMDxgAWNjBf55uU,157
tangle_cnn/nissl_to_multichannel.py,sha256=Y198kWL6iH2KWa7aHREJ9ydUOrXU65xhR4lOa9RLqAU,4343
tangle_cnn/osl_worker.py,sha256=c9MykH6kLOF9lA_fumB6zVVqRk7u4134qkdpo1p3LcA,3287
tangle_cnn/unet_wildcat.py,sha256=yvAat25rTIF_JMK7tnItp_5UkrddZbVwWdtbkNI3gPI,7200
tangle_cnn/unet_wildcat_gmm.py,sha256=-xkE2kYqNWQgLxJN7PLwYe8jq77W0vh7UZI2PmA3asQ,23741
tangle_cnn/wildcat_main.py,sha256=1wvQ8Z6xJLeQOl7DEKV6VsieqwjJcbwWD4c7x0HKm6U,46648
tangle_cnn/deepcluster/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
tangle_cnn/deepcluster/clustering.py,sha256=p9B8uQH1g4OYB5aNHOrsXBENQGuRiBFJgsm-95FSf7I,11730
tangle_cnn/deepcluster/eval_linear.py,sha256=v_Pa15jAlTkREGlYzmLQsWIQYs4yFaQwrTydyHX6fAA,11427
tangle_cnn/deepcluster/eval_retrieval.py,sha256=Jt1ZUG4LXK_SZackKq0Ub5vhsSmimaF8yMdPHHyYvfY,19227
tangle_cnn/deepcluster/eval_voc_classif.py,sha256=OFT6KG1TC8R5tnatb5oAiypfFjfmkKyrazOWJ0ZGGLo,10520
tangle_cnn/deepcluster/main.py,sha256=LKa6Le9TRP31gL-2f-6gl076H77bAnycLwLQAUCDlC8,12276
tangle_cnn/deepcluster/util.py,sha256=9Hqvj8t0-A1l24FjEHH3h2znlWaQxcDWPlB5aDpQvUo,3788
tangle_cnn/deepcluster/models/__init__.py,sha256=T0ourKJ_82d11MMpjOoQoSPNk40T7Vn4y-m2UKYIa1U,236
tangle_cnn/deepcluster/models/alexnet.py,sha256=RlRR8p7jBYpC7J4cH7b2MnISyyKNHWUBPWygHqC6A8g,3409
tangle_cnn/deepcluster/models/vgg16.py,sha256=070mduY5wXfE6_GC1RbDKrii93Ucakowfm4I5cgRyu8,3191
tangle_cnn/deepcluster/visu/activ-retrieval.py,sha256=d9H2L2NkWFh5z1Ye4wjOi_4PgwXwqfxU9fSPq8f245w,3875
tangle_cnn/deepcluster/visu/gradient_ascent.py,sha256=bkwL-ALC3uvv6tF6chAsuhcr-d2_3NV0e222Wv4zmfw,4670
tangle_cnn/wildcat_pytorch/picsl_wildcat/gmm.py,sha256=48tO4sjgWVhLI87J9MywYMh7RcTM3Xrf4iKsokqmiv8,27402
tangle_cnn/wildcat_pytorch/picsl_wildcat/losses.py,sha256=_YR_zA06Ii2EYsBIxN20SA7BB_XXvu-d1aI_8vLzAzA,6174
tangle_cnn/wildcat_pytorch/picsl_wildcat/models.py,sha256=HF1ei5hKeubGY3cDSJWwqJwKUta58uWim6kWJc6Id9o,8838
tangle_cnn/wildcat_pytorch/picsl_wildcat/util.py,sha256=CkqeYNl4LFwRpwk6TAML7K9OqY2mqev7h03viNvfsVg,6786
tangle_cnn/wildcat_pytorch/wildcat/__init__.py,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
tangle_cnn/wildcat_pytorch/wildcat/demo_mit67.py,sha256=BUSaniO7iUlprwkCx3_L59vDkh7nrJxGMrrYFknqx-k,3621
tangle_cnn/wildcat_pytorch/wildcat/demo_voc2007.py,sha256=ay9MvJGsBSetH5HxleaKvyw3hFWiaJcWTg9YrcyLa48,3686
tangle_cnn/wildcat_pytorch/wildcat/engine.py,sha256=7OaH8uZrZ9KYcV_ElOcbHgkwvDnzMMpfPqt6ufEmPcY,23115
tangle_cnn/wildcat_pytorch/wildcat/mit67.py,sha256=DBizMkAqd9Z-Cf6ZJjXXDE3kZHZWp3cxoWa2yC6LdTg,4867
tangle_cnn/wildcat_pytorch/wildcat/models.py,sha256=TryPbY0Dojwhsg7Y--46CZ5vIWrZo5r_IVzbqTMYYSI,2097
tangle_cnn/wildcat_pytorch/wildcat/pooling.py,sha256=nYa3vAcRHc9tr_DO4cimq8rUfW8iyMXr8N9CSt368Ro,4876
tangle_cnn/wildcat_pytorch/wildcat/util.py,sha256=EFgv4vH7tqOa98YWRsNxvu3g6HUpLOGf18pGTeITB-w,6538
tangle_cnn/wildcat_pytorch/wildcat/voc.py,sha256=DWQgaPuu7XBhFQBN4mu8zg_alX9OJlCXhO9Ht_ebbqg,8840
tangle_cnn-0.98.0.dist-info/licenses/LICENSE.txt,sha256=OXLcl0T2SZ8Pmy2_dmlvKuetivmyPd5m1q-Gyd-zaYY,35149
tangle_cnn-0.98.0.dist-info/METADATA,sha256=m_AWv-fUZkMaTWYAY2GS-rsFNhrQtgXmqO_Th91A2mA,7001
tangle_cnn-0.98.0.dist-info/WHEEL,sha256=YCfwYGOYMi5Jhw2fU4yNgwErybb2IX5PEwBKV4ZbdBo,91
tangle_cnn-0.98.0.dist-info/top_level.txt,sha256=qptL2deQcHbWHsxom047kfCpjOoE_jl11JCRnAkAZ8I,11
tangle_cnn-0.98.0.dist-info/RECORD,,
